Data conversion services and associated distributed processing system

ABSTRACT

A method for providing data conversion services is disclosed for a distributed processing system. The distributed processing system identifies and utilizes the capabilities of distributed devices connected together through a wide variety of communication systems and networks and utilize those capabilities to organize, manage and distribute project workloads to the distributed devices.

This application is a continuation-in-part application of the followingco-pending applications: application Ser. No. 09/538,543 entitled“DISTRIBUTED PARALLEL PROCESSING SYSTEM HAVING CAPABILITY-BASEDINCENTIVES AND ASSOCIATED METHOD,” application Ser. No. 09/539,023entitled “SWEEPSTAKES INCENTIVE MODEL AND ASSOCIATED SYSTEM,”application Ser. No. 09/539,448 entitled “CAPABILITY-BASED DISTRIBUTEDPARALLEL PROCESING SYSTEM AND ASSOCIATED METHOD,” application Ser. No.09/539,428 entitled “METHOD OF MANAGING DISTRIBUTED WORKLOADS ANDASSOCIATED SYSTEM,” application Ser. No. 09/539,106 entitled “NETWORKSITE TESTING METHOD AND ASSOCIATED SYSTEM,” application Ser. No.09/538,542 entitled “NETWORK SITE CONTENT INDEXING METHOD AND ASSOCIATEDSYSTEM,” and application Ser. No. 09/539,107 entitled “DISTRIBUTEDBACK-UP SYSTEM AND ASSOCIATED METHOD,” each of which was filed on Mar.30, 2000, and each of which is hereby incorporated by reference in itsentirety.

TECHNICAL FIELD OF THE INVENTION

This invention relates to distributing project workloads among adistributed devices and more particularly to techniques and relatedmethods for managing, facilitating and implementing distributedprocessing in a network environment.

BACKGROUND

Prior processing systems have included the technique of multiple userswithin a company sharing processing time available on a mainframe orcentral processing system. Using small segments of mainframe processingtime, departments within the company would often incur costs associatedwith using the processing time, which in turn was billed back to eachdepartment from the central information technology (IT) organization forthe company. In other instances, a company could pay for and utilizeprocessing time made available by third-party companies who possessed anover-capacity of mainframe processing power. These third-party companieswould, in effect, create a market for the mainframe processing time thatwent unused by the internal organizations of that third-party company.

Prior processing techniques have also included distributed processingprojects that have utilized the Internet or World Wide Web. Thesedistributed processing research projects have used personal computers(PCs) connected to the Internet to provide processing power toaccomplish research project goals. Research project goals have been, forexample, identifying large prime numbers, analyzing radio telescopedata, and analyzing code keys in an encryption deciphering contest.

One example of a distributed processing project on the Internet is aresearch project housed at the University of California at Berkeley toanalyze sky recording data gathered by SETI (the Search forExtraterrestrial Intelligence). This sky recording data has beengathered for some time from the large Arecibo Radio Telescope in PuertoRico. The processing power needed to analyze these data recordings wasvery large. At the peak of SETI's capture activities, SETI hadaccumulated over 100,000 years of signals to process, as measured by thecompute power necessary to process all the signals. To analyze thisdata, software was developed that could be downloaded to Internetconnected PCs so that these PCs could process small slices of these skyrecordings. In under a year, this project, called SETI@home (URL inMarch 2000—www.setiathome.ssl.berkeley.edu) has completely processedthis backlog of data and is now returning to the sky recording datasetfor further processing tasks. This massively parallel distributed systemhas a processing throughput of over 10 TFLOPs (terraFLOPS or 10¹²floating point operations per second) running on about 1.8 millionInternet connected machines.

Another example of a distributed processing technique was developed andimplemented by Distributed.net (URL in March 2000—www.distributed.net)to compete in encryption breaking contests. Distributed.net created anddistributed a client software program which may be downloaded by clientsystems connected to the Internet. This client software then acts aspart of a large distributed processing system specifically designed tobreak encrypted messages on the Internet. Using this processingtechnique, Distributed.net has won encryption breaking contestssponsored by RSA Labs, which is an Internet security company. In thesecontests, RSA Labs has offered a monetary prize to the winner of theencryption contest. In organizing its efforts, Distributed.net hasoffered a share of this monetary prize to the client system thatactually breaks the encryption code. In addition, Distributed.net keepstrack of overall project statistics, as well as statistics concerningthe efforts of its client systems through individual and team rankingsby amount of processing completed.

Entropia.com (URL in March 2000—www.entropia.com) has utilized anInternet distributed processing system to compete in contests directedto identifying the largest prime number. Entropia.com also offers itscomputing power to other research projects. Users may sign on to be partof the distributed processing for free. For the largest prime numbercontest, Entropia.com, like Distributed.net, offers a monetary prize tothe Internet connected PC that comes up with the first prime numberachieved in a new order of magnitude. For other research projects, theincentive is simply to be a part of the research project.

Another distributing processing web site is provided by Process TreeNetwork (URL in March 2000—www.processtree.com). This web site isattempting to sign-up Internet connected computer systems to provideprocessing power for paying projects. For a project, each partnersystem, when connected to the Internet, will have client software thatdownloads a job unit and processes that job unit. The incentive offeredby the Process Tree Network are “micro-payments” for the amount of workcompleted by any given system. These micro-payments are apparently smallamounts of some total project value based upon the amount of the projectcompleted by the given system through the jobs it has processed. Inaddition, each partner is given a bonus percentage of payments made topersons they sign-up as new partners.

In completely unrelated Internet activities outside the distributedprocessing arena, there have been a number of sites that have utilized asweepstakes model as an incentive for consumer behavior. One of the mostpopular (as of March 2000) sweepstakes sites is IWON.COM (URL as ofMarch 2000—www.iwon.com). IWON.COM is a standard Internet search andcontent portal that provides an incentive to users by giving thementries to a sweepstakes when the users use the portal. The more theusers use the portal, the more entries the user generates, up to alimit, for example, up to 100/day. As of March 2000, at the end of eachday, IWON.COM chooses a $10,000 winner from among the entries. At theend of each month, IWON.COM chooses a $1,000,000 winner. And, at the endof an overall sweeps period (as of March 2000), IWON.COM plans to draw asingle winner for a $10,000,000 grand prize. IWON.COM has created thissweepstakes model to introduce an Internet portal in late 1999 and makeit a web site that has as a comparable number of people using it as doesInternet portals that have existed for many years, such as, for example,Yahoo.com (URL in March 2000—www.yahoo.com).

Significantly, these prior distributed processing projects have failedto fully utilize the capabilities of connected distributed devices.

SUMMARY OF THE INVENTION

The present invention provides data conversion services for adistributed parallel processing system that identifies the capabilitiesof distributed devices connected together through a wide variety ofcommunication systems and networks and utilizes those capabilities toorganize, manage and distribute project workloads to the distributeddevices.

In one embodiment, the present invention is a method of operating adistributed processing system to provide data conversion services,including providing a server system, coupling the server system to anetwork that is configured to be coupled to distributed devices,receiving a request for data conversion from a requesting device, andutilizing the server system to distribute workloads to at least onedistributed device to accomplish the requested data conversion. Moreparticularly, the data conversion includes language translation ornetwork site content reformatting.

In another embodiment, the present invention is, a method of operating adistributed processing system to provide data conversion services,including providing a server system, coupling the server system to anetwork that is configured to be coupled to distributed devices,receiving a request for data conversion service from a requestingdevice, and allocating at least one distributed device to accomplish therequested data conversion service. More particularly, the requestingdevice comprises a network site content server, and the network is theInternet. Still further, the allocating step may include allocating agroup of distributed devices for a period of time to accomplish expecteddata conversion demands on the requesting device.

In a further embodiment, the present invention is a distributed dataconversion processing system, including a first system coupled to anetwork that is configured to be coupled to distributed devices, and adatabase storing capability vectors for a plurality of the distributeddevices. The first system receiving data conversion requests from arequesting device and utilizing at least one capability vector toidentify at least one distributed device to accomplish data conversion.

DESCRIPTION OF THE DRAWINGS

It is noted that the appended drawings illustrate only exemplaryembodiments of the invention and are, therefore, not to be consideredlimiting of its scope, for the invention may admit to other equallyeffective embodiments.

FIG. 1A is a block diagram for a distributed processing system havingclient capability and incentive features, according to the presentinvention.

FIG. 1B is a block diagram for information flow among customer systems,server systems and client systems, according to the present invention.

FIG. 2A is a block diagram for a client system, according to the presentinvention.

FIG. 2B is a block diagram for processing elements within a clientsystem, according to the present invention.

FIG. 2C is a block diagram for a client system agent installed on aclient system, according to the present invention.

FIG. 2D is an example user interface for a client system agent,including incentive advertising, according to the present invention.

FIG. 3A is a block diagram for server systems, according to the presentinvention, including a control system, a sweepstakes system and aworkload database.

FIG. 3B is a block diagram for servers systems, customer systems, clientsystems and outsourced host systems, according to the present invention.

FIG. 3C is a block diagram for a server system processor, according tothe present invention.

FIG. 3D is an alternative block diagram for a server system processor,according to the present invention.

FIG. 4 is a functional block diagram for an example sweepstakesincentive operation according to the present invention.

FIG. 5A is a block diagram for a distributed processing system for anetwork site indexing application, according to the present invention.

FIG. 5B is a functional block diagram for an indexing operationaccording to the present invention.

FIG. 6A is a block diagram for a server system according to the presentinvention, including a control system, a workload database, and adatabase of client capabilities balancing vectors.

FIG. 6B is a functional block diagram for client capabilities balancingof workloads according to the present invention.

FIG. 7A is a block diagram for a distributed processing system,according to the present invention, including example network sites onwhich site testing is to be conducted, such as load testing and/orquality-of-service (QoS) testing.

FIG. 7B is a functional block diagram for site-testing, according to thepresent invention.

FIG. 8 is a block diagram of a distributed processing system for a databackup application, according to the present invention.

FIG. 9 is a block diagram of an alternative representation of aninterconnection fabric for a distributed processing system environment,according to the present invention.

FIG. 10 is a block diagram of a more detailed block diagram for a clientsystem agent installed on a client system, according to the presentinvention.

FIG. 11A is a more detailed flow diagram for machine generatedsweepstakes entries according to the present invention.

FIG. 11B is an alternative detailed flow diagram for machine generatedsweepstakes entries according to the present invention.

FIG. 12A is a block diagram of a distributed processing system thatallows customers to select client system attributes, according to thepresent invention.

FIG. 12B is a block flow diagram for client system attribute selection,according to the present invention.

FIG. 13A is a block diagram of a distributed processing system thatprovides data conversion services, according to the present invention.

FIG. 13B is a block flow diagram for data conversion services within adistributed processing system, according to the present invention.

FIG. 14A is a block diagram of a distributed processing system thatprovides data transmission caching, according to the present invention.

FIG. 14B is a block diagram of a distributed processing system thatprovides data sharing and file distribution, according to the presentinvention.

FIG. 15 is a block diagram of an alternative representation for adistributed processing system, according to the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention contemplates the identification of thecapabilities of distributed devices connected together through a widevariety of communication systems and networks and the aggregation ofthese capabilities to accomplish processing, storage, broadcasting orany other desired project objective. For example, distributed devicesconnected to each other through the Internet, an intranet network, awireless network, home networks, or any other network may provide any ofa number of useful capabilities to third parties once their respectivecapabilities are identified, organized, and managed for a desired task.These distributed devices may be connected personal computer systems(PCs), internet appliances, notebook computers, servers, storagedevices, network attached storage (NAS) devices, wireless devices,hand-held devices, or any other computing device that has usefulcapabilities and is connected to a network in any manner. The presentinvention further contemplates providing an incentive, which may bebased in part upon capabilities of the distributed devices, to encourageusers and owners of the distributed devices to allow the capabilities ofthe distributed devices to be utilized in the distributed parallelprocessing system of the present invention.

The number of usable distributed devices contemplated by the presentinvention is preferably very large. Unlike a small local networkenvironment, for example, as may be used by an Internet Service Provider(ISP), which may include less than 100 interconnected computers systemsto perform the tasks required by the ISP, the present inventionpreferably utilizes a multitude of widely distributed devices to providea massively distributed processing system. With respect to the presentinvention, a multitude of distributed devices refers to greater than1,000 different distributed devices. With respect to the presentinvention, widely distributed devices refers to a group ofinterconnected devices of which at least two are physically located atleast 100 miles apart. With respect to the present invention, amassively distributed processing system is one that utilizes a multitudeof widely distributed devices. The Internet is an example of ainterconnected system that includes a multitude of widely distributeddevices. An intranet system at a large corporation is an example of aninterconnected system that includes multitude of distributed devices,and if multiple corporate sites are involved, may include a multitude ofwidely distributed devices. A distributed processing system according tothe present invention that utilizes such a multitude of widelydistributed devices, as are available on the Internet or in a largecorporate intranet, is a massively distributed processing systemaccording to the present invention.

FIG. 1A is a block diagram for a distributed parallel processing system100 according to the present invention. The network 102 is shown havinga cloud outline to indicate the unlimited and widely varying nature ofthe network and of attached client types. For example, the network 102may be the Internet, an internal company intranet, a local area network(LAN), a wide area network (WAN), a wireless network, a home network orany other system that connects together multiple systems and devices. Inaddition, network 102 may include any of these types of connectivitysystems by themselves or in combination, for example, computer systemson a company intranet connected to computer systems on the Internet.

FIG. 1A also shows client systems 108, 110 . . . 112 connected to thenetwork 102 through communication links 118, 120 . . . 122,respectively. In addition, server systems 104, other systems 106, andcustomer systems 152 are connected to the network 102 throughcommunication links 114, 116 and 119, respectively. The client systemcapabilities block 124 is a subset of the server systems 104 andrepresents a determination of the capabilities of the client systems108, 110 . . . 112. The incentives block 126 is also a subset of theserver systems 104 and represents an incentive provided to the users orowners of the clients systems 108, 110 . . . 112 for allowingcapabilities of the clients systems 108, 110 . . . 112 to be utilized bythe distributed processing system 100. The client systems 108, 110 and112 represent any number of systems and/or devices that may beidentified, organized and utilized by the server systems 104 toaccomplish a desired task, for example, personal computer systems (PCs),internet appliances, notebook computers, servers, storage devices,network attached storage (NAS) devices, wireless devices, hand-helddevices, or any other computing device that has useful capabilities andis connected to a network in any manner. The server systems 104represent any number of processing systems that provide the function ofidentifying, organizing and utilizing the client systems to achieve thedesired tasks.

The incentives provided by the incentives block 126 may be any desiredincentive. For example, the incentive may be a sweepstakes in whichentries are given to client systems 108, 110 . . . 112 that are signedup to be utilized by the distributed processing system 100. Otherexample incentives are reward systems, such as airline frequent-flyermiles, purchase credits and vouchers, payments of money, monetaryprizes, property prizes, free trips, time-share rentals, cruises,connectivity services, free or reduced cost Internet access, domain namehosting, mail accounts, participation in significant research projects,achievement of personal goals, or any other desired incentive or reward.

As indicated above, any number of other systems may also be connected tothe network 102. The element 106, therefore, represents any number of avariety of other systems that may be connected to the network 102. Theother systems 106 may include ISPs, web servers, university computersystems, and any other distributed device connected to the network 102,for example, personal computer systems (PCs), internet appliances,notebook computers, servers, storage devices, network attached storage(NAS) devices, wireless devices, hand-held devices, or any otherconnected computing device that has useful capabilities and is connectedto a network in any manner. The customer systems 152 representscustomers that have projects for the distributed processing system, asfurther described with respect to FIG. 1B. The customer systems 152connect to the network 102 through the communication link 119.

It is noted that the communication links 114, 116, 118, 119, 120 and 122may allow for communication to occur, if desired, between any of thesystems connected to the network 102. For example, client systems 108,110 . . . 112 may communicate directly with each other in peer-to-peertype communications. It is further noted that the communication links114, 116, 118, 119, 120 and 122 may be any desired technique forconnecting into any portion of the network 102, such as, Ethernetconnections, wireless connections, ISDN connections, DSL connections,modem dial-up connections, cable modem connections, fiber opticconnections, direct T1 or T3 connections, routers, portal computers, aswell as any other network or communication connection. It is also notedthat there are any number of possible configurations for the connectionsfor network 102, according to the present invention. The client system108 may be, for example, an individual personal computer located insomeone's home and may be connected to the Internet through an InternetService Provider (ISP). Client system 108 may also be a personalcomputer located on an employee's desk at a company that is connected toan intranet through a network router and then connected to the Internetthrough a second router or portal computer. Client system 108 mayfurther be personal computers connected to a company's intranet, and theserver systems 104 may also be connected to that same intranet. Inshort, a wide variety of network environments are contemplated by thepresent invention on which a large number of potential client systemsare connected.

FIG. 1B is a block diagram for information flow 150 among customersystems 152, server systems 104 and client system 134, according to thepresent invention. The server systems 104, as discussed above, mayinclude any number of different subsystems or components, as desired,including client system capabilities block 124 and incentives block 126.The server systems 104 send project and benchmark workloads 130 toclient systems 134. A benchmark workload refers to a standard workloadthat may be used to determine the relative capabilities of the clientsystems 134. A project workload refers to a workload for a given projectthat is desired to be completed. The project workload may be, forexample, a workload for projects such as network site content indexing,network site testing including network site load testing and networksite quality of service testing, data back-up, drug design, druginteraction research, chemical reaction studies, bioinformaticsincluding genetic and biological analyses, human genome analyses,pair-wise comparisons including fingerprint and DNA analyses, datamining, internet hosting services, intranet hosting services, auctionservices, market clearing services, payment systems, bioinformaticsimulations, knowledge management services, trading services, datamatching services, graphics rendering, or any other desired project.

Client systems 134, as discussed above, may be any number of differentsystems that are connected to the server systems 104 through a network102, such as client systems 108, 110 . . . 112 in FIG. 1A. The clientsystems 134 send results 132 back to the server systems 104 after theclient systems 134 complete processing any given workload. Dependingupon the workload project, the server systems 104 may then provideresults 156 to customer systems 152. The customer systems 152 may be,for example, an entity that desires a given project to be undertaken,and if so, provides the project details and data 158 to the serversystems 104.

FIG. 2A is a block diagram for an example client system 108 according tothe present invention. In this simplified block diagram, an originalworkload 204 is received through line 208 from an interface 206. Theoriginal workload 204 represents a portion of the processing, storage orother activity required to complete the desired task for which theserver system 104 is trying to accomplish. This original workload 204 issent by the server system 104 through the network 102 and received bythe client system 108 through communication link 118. The client system108 processes the original workload 204. Following line 212, results 202are then stored for transferring along line 210 to interface 206.Interface 206 may then communicate the results back to the server system104 through communication line 118, or to other client systems (forexample, with peering of client systems) and then through the network102.

It is noted that the workload received by client system 108 and theprocessing or activity performed may depend up a variety of factors, asdiscussed further below. In part, this workload allocated by the serversystem 104 to each client system 108, 110 and 112 may depend upon thecapabilities of the client system, such as the processing power, diskstorage capacity, communications types, and other capabilities availablefrom the various components of the systems within the client system 108.

The server systems 104 can select the workloads for the client system108 and may control when these workloads are performed, throughoperational code (i.e., an agent) residing and installed on the clientsystem 108. Alternatively, the owner or user of the client system 108may determine when workloads are procured or obtained from the serversystems 104, as well as when these workloads are performed, for example,by accessing the server systems 104 through the network 102. Forexample, the sever system 104 may download to the client system 108 uponrequest one or more workloads. At the same time, an agent residing onthe client system 108 may operate to process the workload or multipleworkloads downloaded to the client system 108. It is noted, therefore,that the agent may be simultaneously managing more than one workload forany number of projects. When the workload is complete, the agent mayinform the owner or user of the client system 108 the results are readyto be communicated back. The client system 108 may then upload resultsto the server system 104 and download new workloads, if desired.Alternatively, these logistical and operational interactions may takeplace automatically through control of the agent and/or the serversystems 104.

FIG. 2B is a block diagram for processing elements within a clientsystem 108 according to the present invention. In this diagram, clientsystem 108 is contemplated as a personal computer. In a personalcomputer, an internal bus 260 would typically have a variety ofdifferent devices connected to it. For example, a CPU 250 could beconnected through the bus 260 to a video processor 252, a floating pointprocessor 254 (often integrated within the CPU itself), and digitalsignal processors (DSPs), such as those found on sound cards and modems.In addition, any of a variety of other processing devices 258 may beincluded. Furthermore, other types of devices may be connected, such ashard drives 264, which provide disk storage capabilities, and a digitalcamera 262.

It is noted, therefore, that the capabilities for client systems 108,110 . . . 112 may span the entire range of possible computing,processing, storage and other subsystems or devices that are connectedto a system connected to the network 102. For example, these subsystemsor devices may include: central processing units (CPUs), digital signalprocessors (DSPs), graphics processing engines (GPEs), hard drives(HDs), memory (MEM), audio subsystems (ASs), communications subsystems(CSs), removable media types (RMs), and other accessories withpotentially useful unused capabilities (OAs). In short, for any givencomputer system connected to a network 102, there exists a variety ofcapabilities that may be utilized by that system to accomplish itsdirect tasks. At any given time, however, only a fraction of thesecapabilities are typically used on the client systems 108, 110 . . .112. The present invention can take advantage of these unusedcapabilities.

It is also noted that along with receiving the workload, the clientsystem 108 will also receive an agent that manages the completion of theworkload. This agent may be software that is customized for theparticular computer system and processing capabilities of the clientsystem 108. For example, if the client system is a personal computer asshown in FIG. 2B, the agent may be a program that operates in thebackground of the computer's operating system. When the agent determinesthat there is unused processing or other capabilities, the agent maytake advantage of it. For example, if the user is using a wordprocessing application to create a document, little processing power isbeing utilized by the word processing program, leaving the computer'sCPU and video processor underutilized. Thus, the agent could executecommands to these processors during dead cycles. In this way, the agentmay facilitate the completion of workload processing in a reduced time.In addition, this agent may be self-updating upon connecting to theserver systems 104, so that the agent may be kept up to date withcurrent software revisions and workload activities. It is also notedthat the agent may manage work on multiple workloads at the same time,so that any given distributed device connected to the network 102 may beworking on a plurality of workloads at any given time.

FIG. 2C is a block diagram for an example client system agent 270. Theagent 270 may include a security subsystem 272 that controls theinterface of the client system 108 with the agent 270. The securitysubsystem 272 may help keep the workloads secure and may help to keepthe client systems 108 from suffering any security problems incompleting the workload. For example, the agent 272 may operate to keepviruses from attacking the client system 108 while the client system 108is processing the workload through the operation of the agent. Thesecurity subsystem 272, therefore, may provide the interface for theworkloads 130 and the results 132.

The clients system agent 270 may also include a workload engine 274, astatistics/user interface/incentive advertising block 276, and aworkload package and update processing block 278. In the example shownin FIG. 2C, workloads 130 pass through the security subsystem 272 andalong line 280 to the workload package and update processing block 278.In this block 278, the agent 270 may be updated by the server systems104. Alternatively, the agent 270 may determine, when connected to theserver systems 104, whether it needs to be updated and then accomplishthat updating automatically. Once the workload package is processed, theworkload engine 274 may receive the workload following line 288. Theworkload engine 274 works on the workload, ultimately completing theworkload. The results or status of the workload may then be sent throughthe security subsystem 272 following line 282. The results 132 may thenbe provided back to the server systems 104.

The statistics/user interface/incentive advertising block 276 mayprovide workload, incentive and other statistics, as well as any otherdesired interface features, to the user of the client system. Forexample, the block 276 may show a user the expected amount of processingtime it will take for the client system to complete a workload taskbased upon the capabilities of the system. As also shown, the block 276may receive information following lines 286 and 284 from the workloadpackage and update processing block 278 and from the workload engine274. If desired, security information from the security subsystem 272could also be displayed to the user of the client system. It is notedthat the information displayed to the user of the client system may bemodified and selected as desired without departing from the presentinvention.

With respect to incentive advertising, the block 276 may also show theuser of the client system how this processing time might changedepending upon various possible upgrades to the capabilities of theclient system, such as a faster microprocessor, more memory, more diskstorage space, etc. Furthermore, the client system capabilities may beshown correlated to the incentives provided to the client system forparticipation. Thus, the user may be provided information as to how theuser's incentives would increase or change depending upon other computersystems or upgraded capabilities the user could acquire. This incentivevalue increase may also be tied to upgrades to particular vendor'sdevices. For example, if the user's device is a computer system havingan ABC microprocessor, the block 276 may provide the user information asto increased incentive values based upon an upgrade to a more powerfulABC microprocessor. Similarly, if the user's device is a computer systemobtained from ABC, the block 276 may provide the user information as toincreased incentive values based upon an upgrade to a more powerful ABCcomputer system.

FIG. 2D is a an example user interface 276 for a client system agent,including incentive advertising, according to the present invention. Inthe example shown, interface 276 is a window 230 that may be displayedon a distributed device, for example, a computer system. This window 230displays the desired information for the agent client manager. Asindicated above, this agent client manager is initially downloaded fromthe server systems 104 and thereafter may be updated at various timeswhen the client system is communicating with the server systems. Theinterface 276, as shown, includes interface tabs 221, 222, 224, 226,228, 244, 246 and 248. These interface tabs may be selected through theuser of a pointing device or keyboard attached, for example, to acomputer system graphically displaying the window 230. It is noted thatthe interface tabs 221, 222, 224, 226, 228, 244, 246 and 248 are onlyexamples, and the number, arrangement and content of tabs may bemodified as desired. In addition, the example user interface 276depicted in FIG. 2D is only an example and may be modified as desired.

In FIG. 2D, the processor values interface tab 224 is the one currentlyselected by the user. This tab 224 (Processor Values) includes exampleinformation that may be displayed to the user. Assuming that a workloadis being processed by the agent client manager, the user may select thebutton 242 (Show My Incentive Values) to show the user's currentincentive values associated with the workload being performed. Thepersonal incentive values chart 232 (My Personal Incentive Values) maythen be displayed to the user. As shown, the incentive values areprovided in a relative scale from 1 to 10. The key designation 240represents the incentives associated with the users current centralprocessing unit (CPU) or microprocessor.

As indicated above, this incentive information may also be tied to thespecific vendor of the user's CPU, for example, ABC Company's CPU. Thus,as shown, the key designation 240 (My current processor) and thecorresponding bar graph portion 236 represent incentives for the user'scurrent CPU (e.g., a 166 MHz processor). The key designation 238represents the incentives that the user is projected to have if the userwere to upgrade the CPU. Again, this upgrade incentive information maybe tied to the specific vendor of the user's CPU or to any other vendor,if desired. Thus, as shown, the key designation 238 (NEW ABC 1 GHzprocessor!) and the corresponding bar graph portion 234 representincentives for an upgrade to a new ABC CPU (e.g., a new ABC 1 GHzprocessor). In this manner, a user may be provided an incentive toincrease the capabilities of the distributed device, and a vendor may beprovided advertising so that the user is also directed to a particularupgrade.

Looking further to FIG. 2D, other similar incentive related informationtabs may be provided for any desired capability of the distributeddevice. For example, tab 246 (Memory Values) represents information thatmay be provided for the memory capabilities of the distributed device.Tab 224 (Graphics Values) represents information that may be providedfor the graphics capabilities of the distributed device. Tab 226(Communications Values) represents information that may be provided forthe communication capabilities of the distributed device. Tab 228(Storage Values) represents information that may be provided for thestorage capabilities of the distributed device. Tab 248 (System Values)represents information that may be provided for the system capabilitiesas a whole for the distributed device.

In addition to these incentive related information tabs, other tabs maybe included to provide information and control for any desired featuresof the agent client manager. For example, the tab 244 (Current: PrimeSearch) represents information that may be displayed to the user aboutthe current workload being performed by the agent client manager, forexample, a search for large prime numbers. The tab 221 (Settings)represents information that may be displayed to the user about varioussettings for the client agent manager. In particular, the tab 221 mayprovide the user the ability to control any desired aspect of theoperation of the agent client manager. For example, the user may be ableto select a portion of the capabilities that may be utilized (e.g., amaximum of 20% of the system memory), the types of workloads that may beperformed (e.g., only scientific research projects), the times when theagent may utilize system resources (e.g., only between 12 to 6 am, oronly when the system is idle), or any other desired operational feature.It is noted that in addition to upgrade incentive information indicatedabove, the user may also be provided information as to how incentiveswould increase if the user allocated or changed the settings for theagent client manager.

This user selection of operational features allows for workloads to bescheduled or balanced based upon user input and desires. These uservectors, as indicated above, would allow users to dedicate their devicecapabilities to specific research projects (cancer, Parkinson's disease,Internet, genetics, space science, etc.), to specific non-profit or forprofit organizations (Greenpeace, Celera, etc.), educationalinstitutions (University of Texas), a specific group of like mindedusers, or any other entity or endeavor. This affiliation selectionallows the distributed processing system to automatically include auser's device capabilities in a pool dedicated to the chosenaffiliation. Additionally, a user could choose to mix variouspercentages and allocations of device capabilities among multipleaffiliations. It is noted that the user need not make any affiliationselection and need not allocate 100 percent of device capabilities.Rather, only a portion of the device capabilities may be allocated to aparticular affiliation, leaving the remainder non-allocated and notaffiliated. The capability allocation may also be a system-wide (i.e.,course) allocation, such as some desired percent of overall devicecapabilities. The capabilities allocation may also be subsystem specific(i.e., fine) allocation, such as allocation of particular subsystemcapabilities to particular affiliations.

Now looking to FIG. 3A, the server systems 104 may be one or morecomputer systems that operate to identify client system capabilities,organize workloads, and utilize client systems to accomplish a desiredtask. The server systems 104 includes a control system 304 a workloaddatabase 308, and a sweepstakes system 306, as discussed more below. Theworkload database 308 stores any desired project task, which may bebroken up into discrete workload tasks WL1, WL2 . . . WLN, asrepresented by elements 336, 338 . . . 340. The workload database mayalso store one or more benchmark workloads (BWL) 335 that may beutilized to determine client system capabilities in response to astandard workload. Through line 312, the workload database 308communicates with control system 304. Control system 304, for example,receives original workload 322 and transfers it to the interface 320through line 330. The interface 320 then transfers the workload 322 tothe network 102 through line 114. This workload 322 is ultimatelyreceived as workload 204 by client system 108, 110 or 112, as shown inFIG. 2A. The result 324 is ultimately received by the control system 304through interface 320 and line 328.

In allocating workloads, the control system 304 may consider thecapabilities of the client systems 108, 110 and 112 to which the controlsystem 304 is sending workloads. For example, if client 108 has moreprocessing power than client 110, the control system 304 may allocateand send more difficult or larger workloads. Thus, client 108 mayreceive WL1 336 and WL2 338, while client 110 would only receive WL3.Alternatively, the workload database 308 could be organized withdiffering levels of processing power or capability requirements for eachworkload. In this way, WL1 336 may represent a greater processing orsystem capability requirement than WL2 338. It should be noted thatworkload may be a processing task, a data storage task, or tied to anyother of a variety of capabilities that may be utilized on the clientsystems 108, 110 . . . 112.

As indicated above, to encourage owners or users of client systems toallow their system capabilities to be utilized by control system 104, anincentive system may be utilized. This incentive system may be designedas desired. Incentives may be provided to the user or owner of theclients systems when the client system is signed-up to participate inthe distributed processing system, when the client system completes aworkload for the distributed processing system, or any other time duringthe process. In addition, incentives may be based upon the capabilitiesof the client systems, based upon a benchmark workload that provides astandardized assessment of the capabilities of the client systems, orbased upon any other desired criteria.

One example use of a benchmark workload is to use the benchmark workloadto determine incentive values. For example, the server systems 104 maybe designed to send out a standard benchmark workload once an hour toeach client system 108, 110 . . . 112. If a client system is notavailable at that time for any reason, the workload would not becompleted by the client system, and there would be no incentive valuegenerated for that client system. In this example, the benchmarkworkload may be a timed work-set that would exercise each subsystem withcapabilities within the client system that was desired to be measured. Amore capable client system would then generate greater incentive valuesfrom executing the benchmark workload, as compared to a lesser capableclient system. These incentive values may be utilized as desired todetermine what the client system should get in return for its efforts.For example, if the incentive were a sweepstakes as discussed furtherbelow, the number of entries in the sweepstakes may be tied to thesystem's performance of the benchmark workload. Thus, the faster orbetter the client system performs the benchmark workload, the moreentries the client system would receive.

In the embodiment shown in FIG. 3A, the server systems 104 includes asweepstakes system 306 that functions with control system 304 to provideincentives for the users or owners of client systems 108, 110 and 112 toallow their system capabilities to be used by the server systems 104.The control system 304 may determine a sweepstakes entry value 302 thatis sent along line 310 to the sweepstakes system 306. The sweepstakessystem 306 may then receive sweepstakes entry 332 and provide it to thesweepstakes engine 330 through line 334. The sweepstakes engine 330 mayprocess the entries and determine a winner, when desired. In theembodiment shown, therefore, entries to the sweepstakes may be generatedeach time a unit of work is accomplished by one or more of thesubsystems within a client system 108, 110 or 112 via an agent installedon the device for the purposes of managing and completing units of work.The total entries for any period of time would, therefore, be dynamicdepending on how many are received. Odds of winning would then bedetermined by the total number of entries received and the total numberof entries contributable to any given entrant.

FIG. 3B is another example block diagram of a distributed processingsystem 300 including servers systems 104, customer systems 152, clientsystems 134 and out-sourced host systems 340, according to the presentinvention. The servers systems 104 may include an analytic subsystem346, a results/workload production subsystem 344, a projectpre-processing subsystem 342, a client agent subsystem 243, and anincentive advertising subsystem 245. The incentive advertising subsystem245 may operate to provide advertising information, for example, theupgrade incentive information as discussed with respect to FIG. 2D. Theclient agent subsystem 243 may operate to download an agent to theclient systems 134 and to update this agent at times when the serversystems 104 are communicating with the client systems 134.

The customer systems 152, which represent customers that have projectsthat they desired to be processed by the distributed processing system,may be connected to the project pre-processing subsystem 342 to provideprojects to the servers systems 104. These projects are processed by theproject pre-processing subsystem 342 and passed to the results/workloadsproduction subsystem 344, which produces and sends out workloads 130 andreceives back results 130. The analytic system 346 then takes theresults and processes them as desired. Completed project information maythen be provided from the analytic system 346 to the customer systems152. In this manner, the projects of the customer systems 152 may beprocessed and project results reported by the distributed processingsystem of the present invention.

Also, as shown, the workloads 130 and the results 132, or other tasks ofthe server systems 104, may be processed and handled by out-sourced hostsystems 340, if desired. Thus, some or all of the workloads 130 may besent first to out-sourced host systems 340. Out-sourced host systems 340then send workloads 130A to the client systems 134 and receive backresults 132A. The out-sourced host systems 340 then send the results 132back to the server systems 104. It is noted that this out-sourcing ofserver system tasks may be implemented as desired for any given taskthat the server systems 104 may have. It is further noted that, ifdesired, the server systems 104 may perform all of the desired functionsof the server systems 104 so that no out-sourced host systems 340 wouldbe used.

FIG. 3C is a block diagram for one embodiment of a server systemprocessor 350, according to the present invention. An agent abstractionlayer 360 may send workloads 130 and receive results 132. The securitysubsystem 354 may interact with the agent abstraction layer 360 andprovide information to a data parser 352 and an application programminginterface (APIs) block 356. The APIs block 356, the data parser 352 anda workload manager 558 may interact to accomplish the desired tasks forthe server system processor 350. It is noted that for this embodiment,the API protocol could be controlled and provided to other host systems.

FIG. 3D is an alternative block diagram for a server system processor350, according to the present invention. In this embodiment, the APIsblock 356 and the agent abstraction layer 360 are not present. The dataparser 352, the workload manager 358 and the security subsystem 354interact to provide the desired server system tasks. It is noted thatfor this embodiment, the security subsystem is controlled and utilizedfor communicating with client systems.

FIG. 4 is a functional block diagram for a sweepstakes operation 400 bythe system server 104 according to the present invention. In block 402,the server systems 104 may sign-up client systems in “accept clients”block 402. Following line 418, the server systems 104 identifies thecapabilities of the client's computer and processing systems in the“determine client system capabilities” block 404. Control passes alongline 420 to the “distribute workloads to client systems” block 406,where the server systems 104 allocates workloads to each client system108, 110 and 112. This workload may also be an benchmark workload, asindicated above, that acts as an entry workload to determine the entriesor entry values for the client system. As also indicated above, indistributing the workloads in block 406, the server system 104 may takeinto consideration the capabilities of the client systems to whichworkloads are being distributed. The client systems 108, 110 and 112then operate to complete the workloads allocated to them. The serversystem 104 receives back workload results in “receive workload results”block 408.

At this point, control passes along line 424 to the “determinesweepstakes entries” block 410. In this block 410, the server system 104determines the entry value for the workload completed or for a standardbenchmark or entry workload completed. This entry value may be weightedupon a variety of factors including factors such as the amount of workcompleted, the difficulty level of the processing required, and theaccuracy of the results. It is noted that any desired weighting may beutilized. Thus, it is understood that a wide variety of considerationsmay be utilized to determine the entry value weighting for thesweepstakes.

Although the weighting determination is shown in block 410 in FIG. 4,the entry value may also be determined, in whole or in part, when aclient system signs on to the distributed processing distributed systemof the present invention. For example, if a client system hasstate-of-the-art CPU, video processor, DSP engine, memory, and largeamounts of free disk storage space, a high entry value may be allocatedto this client system up-front. In contrast, a client system that has aslow CPU, a weak video processor, no DSP engine, little memory, andlittle free disk storage space may be allocated a small entry value. Inthis way, the owners or users of the client systems may be providedimmediate feedback as to the potential sweepstakes entry value of theircomputer systems, devices and system capabilities.

It is further noted that the entry value may take any desired form andmay be, for example, a multiplier that will be used for each unit ofworkload completed. In this way, the owner or user will readily becognizant that a state-of-the-art system will yield a high multiplier,where as an older system, system capability or device will yield a lowmultiplier. Such feedback, whether communicated to the owner or userimmediately upon signing up or upon completion of each workload, willcreate an incentive for owners and/or users to acquire state-of-the-artsystems, thereby further increasing the potential processing power ofthe distributed processing system of the present invention.

In addition, different workload projects may be designated withdifferent entry values, as well. For example, some workload projects mayrequire particular hardware or software processing systems within aclient system or device. Thus, the number of client systems that arecapable of performing the task would be limited. To further encourageparticipation by those owners or users with capable systems, the entryvalue for taking on particular workloads and/or systems with the desiredfeatures may be allocated higher entry values.

Referring back to FIG. 4, control passes along line 426 to the “processentries” block 412. In this block 412, the sweepstakes entries areprocessed and stored as desired. Following line 428, “end of entryperiod” decision block 414 represents a determination of whether thetime for getting entries into the sweepstakes has ended. If not, thecontrol continues to line 430 and back to blocks 402, 404 and/or 406,depending upon what is desired. Once the entry period has ended, controlflows along line 432 to “determine winners” block 416. The server system104 then identifies from among the entries, who the winning clientsystem or systems will be.

The entry period may be any desired time frame and may include multipleoverlapping time frames, as desired. For example, winners may bedetermined daily for entries each day, monthly for entries within amonth, and/or yearly for entries within one year. In addition, specialentry periods may be generated, if desired, for example where aparticularly important workload project had a short time frame in whichit needed to be completed.

FIGS. 1, 2A-C, 3A-D, and 4 are directed to example embodiments for adistributed processing system according to the present invention,including a sweepstakes reward or incentive feature, as shown in theembodiments of FIG. 3A and FIG. 4.

FIGS. 6A and 6B further describe a capabilities scheduling feature, inwhich the server systems 104 may identify and consider any of a varietyof client system capability vectors in determining how to organize,allocate and manage workloads and projects. FIGS. 5A and 5B describe adistributed processing system and workload project that accomplishesnetwork site indexing. FIGS. 7A and 7B describe a distributed processingsystem and a workload project that accomplishes network site testing,such as quality of service (QoS) testing and load testing. And FIG. 8describes a distributed processing system, preferably with respect to acorporate intranet, that accomplishes distributed data back-up.

FIG. 9 is an alternative representation for the interconnection fabricfor a distributed processing system environment and describes idleclient system identification and shared component client systems. FIG.10 describes a client system agent installed on a client system. FIGS.11A and 11B further describe machine generated sweepstakes entries.FIGS. 12A and 12B describe client capability selection features. FIGS.13A and 13B describe data conversion services. FIG. 14A describes adistributed processing system that provides data transmission caching.FIG. 14B describes a distributed processing system that provides datasharing and file distribution functions. And FIG. 15 describes analternative representation for a distributed processing system,according to the present invention.

Looking now to FIG. 5A, block diagram is depicted of a distributedprocessing system 550 for a network site indexing application, accordingto the present invention. As stated above with respect to FIG. 1A, thenetwork 102 may be a wide variety of networks. For this network siteindexing application, the network 102 may preferably be the Internethaving a multitude of network sites 552 . . . 554. Each network site 552. . . 554 may have a variety of different content types that may beindexed, ranging from complex sites to relatively simple sites. Forexample, network site 552 includes text 570A, images 570B, audio streams570C, video streams 570D, files 570E and other content 570F. Networksite 554 is less complex and includes text 572A, images 572B, and othercontent 572C. Both network sites 552 and 554 are connected to thenetwork 102 through communication lines 558 and 556, respectively.

As discussed above, the server systems 104 manage workloads for theclient systems 108, 110 . . . 112. The client systems 108, 110 . . . 112process these workloads and produce indexing results. The resultingindex may be stored at a centrally managed site, such as central indexstorage block 560, or may itself be distributed over the possiblymillions of indexing clients 108, 110 . . . 112, as shown by remoteindex storage blocks 562, 564 . . . 566. If remote index storage isutilized, a master database content index may be stored locally, forexample, in the central index storage block 560. This content index maythen direct relevant searches to the distributed massively parallelengine for search queries.

Referring now to FIG. 5B, a functional block diagram is shown for anetwork site indexing operation 500 according to the present invention.As described in FIG. 1A with respect to other systems 106, there may beany number of computer and processing systems connected to the network102. Any one of these others systems 106 may publish information on thenetwork 102 for access by any other system connected to the network 102.This information to be indexed may take a wide variety of forms,including, for example, text, images, audio streams, video streams,databases, spreadsheets, PDF files, Shockwave data, Flash data,applications, data files, chat streams, or any other information, dataor data streams that may be accessible on a network site. Thedistributed processing system of the present invention may have as aworkload the task of indexing this potentially massive amount ofinformation.

For example, where the network 102 is the Internet or a large intranet,a large amount of processing power and time is needed to create anaccurate, complete and up-to-date index of the information. The Internetuses an IP (Internet Protocol) address protocol to direct traffic aroundthe Internet. The IP address is the address of a computer attached to aTCP/IP (Transmission Control Protocol/Internet Protocol) network. Everysystem on the network must have a unique IP address. IP addresses aretypically written as four sets of numbers separated by periods. TheTCP/IP packet uses 32 bits to contain the IP address, which is made upof a network and host address (NETID and HOSTID). The more bits used fornetwork address, the fewer remain for hosts. Web pages within aparticular web site with a unique address may be addressed through URLs(Uniform Resource Locator) associated with that web site. In short,there is a limited, but very large, number of possible IP addresses foruniquely identifiable Internet sites that may be accessed and analyzedto generate an index of Internet sites and web pages via URLs.

The operation diagram of FIG. 5B starts with the “clients receiveindexing workloads” block 502. In this block, the system server 104provides the clients systems 108, 110 . . . 112 with a workload task toindex a portion of the information accessible on the network 102. Forexample, with the Internet, each workload may be single IP address orgroups of URLs or, in some cases, large data types contained on singlesites or pages. Following line 514, the “clients interact with othersystems” block 504 represents the operation of the agent installed onthe client systems 108, 110 . . . 112 to access the network sites,according to the assigned workload, and index the information accessibleon that site. This indexing may include all types of informationaccessible on that site, including text, audio, image, video, etc.

Next, following lines 516 and 518, the client systems 108, 110 and 112complete the workload tasks, get the results ready for transmission, andsends those results back to the system server 104 in “clients completeworkload” block 506 and “indexing results sent to server system” block508. Control passes along line 520 to “index compiled for use” block 510where the server system formats and/or compiles the results for use. Forexample, the index results may be utilized for accurate, complete andup-to-date search information for the network 102. As indicated withrespect to FIG. 5A, the resulting index may be stored remotely orlocally following line 522. Thus, element 524 represents remote storageof the index, and element 526 represents central storage of the index.It is noted that the index may also be stored with a mixture of centraland remote storage, as desired. In addition, as indicated above, adirectory or summary index for the resulting index may be generated andstored centrally, if desired. It is further noted that the summary indexmay be stored in any other desired fashion, for example, it may bedistributed and stored on a number of client systems.

FIG. 6A is a block diagram for a server system 104 according to thepresent invention, including a control system 304, a workload database308, and a database of capability vectors 620. The workload database 308includes a variety of sets of workload projects WL1, WL2 . . . WLN. Foreach workload project, there may be multiple workload units. Forexample, workload project WL1 includes workload units WL11, WL12 . . .WL1N, as represented by elements 640, 642 . . . 644, respectively.Similarly, workload project WL2 includes workload units WL21, WL22 . . .WL2N, as represented by elements 646, 648 . . . 650, respectivelyworkload project WL3 includes workload units WL31, WL32 . . . WL3N, asrepresented by elements 652, 654 . . . 656, respectively.

It may be expected that different workload projects WL1, WL2 . . . WLNwithin the workload database 308 may require widely varying processingrequirements. Thus, in order to better direct resources to workloadprojects, the server system may access various system vectors when aclient system signs up to provide processing time and other system ordevice capabilities to the server system. This capability schedulinghelps facilitate project operation and completion. In this respect, thecapability vector database 620 keeps track of any desired feature ofclient systems or devices in capability vectors CBV1, CBV2 . . . CBVN,represented by elements 628, 630 . . . 632, respectively. Thesecapability vectors may then be utilized by the control system 304through line 626 to capability balance workloads.

This capability scheduling according to the present invention,therefore, allows for the efficient management of the distributedprocessing system of the present invention. This capability schedulingand distribution will help maximize throughput, deliver timely responsesfor sensitive workloads, calculate redundancy factors when necessary,and in general, help optimize the distributed processing computingsystem of the present invention. The following TABLE 1 provides lists ofcapability vectors or factors that may be utilized. It is noted thatthis list is an example list, and any number of vectors or factors maybe identified and utilized, as desired.

TABLE 1 Example Client Capability Vectors or Factors 1. BIOS Support: a.BIOS Type (brand) b. ACPI c. S1, S2, S3, and S4 sleep/wake states d. D1,D2 and D3 ACPI device states e. Remote Wake Up Via Modem f. Remote WakeUp Via Network g. CPU Clock control h. Thermal Management control i.Docked/Undocked state control j. APM 1.2 support k. Hotkey support l.Resume on Alarm, Modem Ring and m. Password Protected Resume from LANSuspend n. Full-On power mode o. APM/Hardware Doze mode p. Stand-by modeq. Suspend to DRAM mode r. Video Logic Power Down s. HDD, FDD and FDCPower Down t. Sound Chip Power Down u. Super I/O Chip Power Down 2. CPUSupport: a. CPU Type (brand) b. MMX instruction set c. SIMD instructionset d. WNI instruction set e. 3DNow instruction set f. Other processordependent instruction g. Raw integer performance set(s) h. Raw FPUperformance i. CPU L1 data cache size j. CPU L1 instruction cache sizek. CPU L2 cache size l. CPU speed (MHz/GHz . . . ) m. System bus(MHz/GHz . . . ) speed supported n. Processor Serial Number o. CPUID 3.Graphic Support a. Graphics type (brand) b. # of graphics engines c.Memory capacity d. OpenGL support e. Direct3D/DirectX support f. Colordepth supported g. MPEG 1/II decode assist h. MPEG1/II encode assist i.OS support j. Rendering type(s) supported k. Single-Pass Multitexturingsupport l. True Color Rendering m. Triangle Setup Engine n. TextureCache o. Bilinear/Trilinear Filtering p. Anti-aliasing support q.Texture Compositing r. Texture Decompression s. Perspectively CorrectTexture Mapping t. Mip-Mapping u. Z-buffering and Double-bufferingsupport v. Bump mapping w. Fog effects x. Texture lighting y. Videotexture support z. Reflection support aa. Shadows support 4. StorageSupport a. Storage Type (brand) b. Storage Type (fixed, removable, etc.)c. Total storage capacity d. Free space e. Throughput speed f. Seek timeg. User dedicated space for current workload h. SMART capable 5. Systema. System Type (brand) b. System form factor (desktop, portable,workstation, server, etc.) 6. Communications Support a. Type ofConnection (brand of ISP) b. Type of Connection Device (brand of c.Hardware device capabilities hardware) d. Speed of connection e. Latencyof connection f. Round trip packet time of connection g. Number of hopson connection type h. Automatic connection support (yes/no) i. Dial-uponly (yes/no) j. Broadband type (brand) k. Broadband connection type(DSL/Sat./Cable/T1/Intranet/etc.) 7. Memory a. Type of memory errorcorrection (none, ECC, etc.) b. Type of memory supported (EDO, c. Amountof total memory SDRAM, RDRAM, etc.) d. Amount of free memory e. Currentvirtual memory size f. Total available virtual memory size 8. OperatingSystem a. Type of operating system (brand) b. Version of operatingsystem c. Health of operating system 9. System application software a.Type of software loaded and/or operating on system b. Version ofsoftware c. Software features enabled/disabled d. Health of softwareoperation

FIG. 6B is a functional block diagram for capabilities determination andscheduling operation 600 for workloads in a distributed processingsystem according to the present invention. Initially, various vectorsare identified for which capability information is desired in the“identify client system capability vectors” block 602. Following line612, the server systems 104 then capability balances workloads amongclient systems 108, 110 and 112 based upon the capability vectors in the“capability scheduling workloads based on vectors” block 604. Then thecapabilities scheduled workloads are sent to the client systems 104 forprocessing in the “send capability scheduled workloads” block 606.

This capability scheduling and management based upon system relatedvectors allows for efficient use of resources. For example, utilizingthe operating system or software vectors, workloads may be scheduled ormanaged so that desired hardware and software configurations areutilized. This scheduling based upon software vectors may be helpfulbecause different software versions often have different capabilities.For example, various additional features and services are included inMICROSOFT WINDOWS '98 as compared with MICROSOFT WINDOWS '95. Any one ofthese additional functions or services may be desired for a particularworkload that is to be hosted on a particular client system device.Software and operating system vectors also allow for customers to selecta wide variety of software configurations on which the customers maydesire a particular workload to be run. These varied softwareconfigurations may be helpful, for example, where software testing isdesired. Thus, the distributed processing system of the presentinvention may be utilized to test new software, data files, Javaprograms or other software on a wide variety of hardware platforms,software platforms and software versions. For example, a Java programmay be tested on a wide proliferation of JREs (Java Runtime Engines)associated with a wide variety of operating systems and machine types,such as personal computers, handheld devices, etc.

From the customer system perspective, the capability management and thecapability database, as well as information concerning users of thedistributed devices, provide a vehicle through which a customer mayselect particular hardware, software, user or other configurations, inwhich the customer is interested. In other words, utilizing themassively parallel distributed processing system of the presentinvention, a wide variety of selectable distributed device attributes,including information concerning users of the distributed devices, maybe provided to a customer with respect to any project, advertising, orother information or activity a customer may have to be processed ordistributed.

For example, a customer may desire to advertise certain goods orservices to distributed devices that have certain attributes, such asparticular device capabilities or particular characteristics for usersof those distributed devices. Based upon selected attributes, a set ofdistributed devices may be identified for receipt of advertisingmessages. These messages may be displayed to a user of the distributeddevice through a browser, the client agent, or any other software thatis executing either directly or remotely on the distributed device.Thus, a customer may target particular machine specific device or userattributes for particular advertising messages. For example, users withparticular demographic information may be targeted for particularadvertisements. As another example, the client agent running on clientsystems that are personal computers may determine systems that aresuffering from numerous page faults (i.e., through tracking operatingsystem health features such as the number of page faults). High numbersof page faults are an indication of low memory. Thus, memorymanufactures could target such systems for memory upgrade banners oradvertisements.

Still further, if a customer desires to run a workload on specificdevice types, specific hardware platforms, specific operating systems,etc., the customer may then select these features and thereby select asubset of the distributed client systems on which to send a projectworkload. Such a project would be, for example, if a customer wanted torun a first set of simulations on personal computers with AMD ATHLONmicroprocessors and a second set of simulations on personal computerswith INTEL PENTIUM III microprocessors. Alternatively, if a customer isnot interested in particular configurations for the project, thecustomer may simply request any random number of distributed devices toprocess its project workloads.

Customer pricing levels for distributed processing may then be tied, ifdesired, to the level of specificity desired by a particular customer.For example, a customer may contract for a block of 10,000 randomdistributed devices for a base amount. The customer may later decide foran additional or different price to utilize one or more capabilityvectors in selecting a number of devices for processing its project.Further, a customer may request that a number of distributed devices bededicated solely to processing its project workloads. In short, oncedevice attributes, including device capabilities and user information,are identified, according to the present invention, any number ofcustomer offerings may be made based upon the device attributes for theconnected distributed devices. It is noted that to facilitate use of thedevice capabilities and user information, capability vectors and userinformation may be stored and organized in a database, as discussedabove.

Referring now to FIG. 12A, a block diagram depicts a distributedprocessing system 1200 that allows customers to select client systemattributes, such as device capabilities and user characteristics,according to the present invention. In this embodiment, the network 102is depicted as the Internet to which server systems 104, customer 152A,customer 152B, and client systems 1202A, 1202B . . . 1202C areconnected. These systems are connected through communication links 114,119A, 119B, 1204A, 1204B . . . 1204C, respectively. As noted above,these communication links may include any of a wide variety of devicesand/or communication techniques for allowing a system to interface withother connected systems.

As shown in FIG. 12A, and as discussed above, the customers 152A and152B may desire to send information or projects, such as advertisements(ADV) 1206A and 1206B and/or projects (PROJ) 1208A and 1208B, to groupsof client systems that have particular or selected capabilities. Thenumber of different groups of client systems is as varied as thecapability and user data available for those client systems. The clientsystems 1202A represent client systems that include a first set (Set 1)of desired attributes. The client systems 1202B represent client systemsthat include a second set (Set 2) of desired attributes. And the clientsystems 1202C represent client systems that include a Nth set (Set N) ofdesired attributes. Once attributes are selected, the client systemswith those attributes may be accessed as desired by customers 152A and152B. For example, customer 152A may send its advertisement to clientsystems 1202B. Customer 152B may send its advertisement to clientsystems 1202A. The project 1208A from customer 152A may be processed byclient systems 1202C. And the project 1208B from customer 152B may beprocessed by client systems 1202B. It is noted, therefore, that anycombination of desired attributes, such as device capabilities and usercharacteristics, may be identified and utilized to satisfy customerobjectives, whether those objectives be advertising, project processing,or some other desired objective.

FIG. 12B is a block flow diagram for client system attribute selection,according to the present invention. In the embodiment shown, process1250 begins with the customer selecting desired attributes in block1252. Next, client systems with selected attributes are accessed inblock 1254. And, then in block 1256, the customer objective, such asadvertising or project, is processed by the client system. Control ofthis process 1250 may be provided by the server systems 104, if desired,such that the customer interfaces with the server systems 104 to selectdevice attributes and then the servers systems 104 access the clientsystems. Alternatively, the server systems 104 may simply provide thecustomer with a list of contact information (e.g., IP addresses) for theclient systems, so that the customer may directly access the clientsystem, for example, in providing advertisements to the users of theclient systems. It is further noted that other control techniques mayalso be used to identify and access client systems with particulardesired device capabilities, user characteristics, or other deviceattributes, according to the client system attribute selection method ofthe present invention.

FIG. 7A is a block diagram for a network 102 according to the presentinvention, including example network sites 106A and 106B on which sitetesting is to be conducted, such as load testing and/orquality-of-service (QoS) testing. FIG. 7A is similar to FIG. 1A exceptthat other systems 106 in FIG. 1A has been represented in the embodimentof FIG. 7A with network sites 106A and 106B. Communication line 116Abetween the network 102 and the network site 106A represents ainteraction by one client system 108, 110 and 112. Communication lines116B, 116C and 116D represent interactions by more than one clientsystem 108, 110 and 112.

Site testing is typically desired to determine how a site or connectedservice performs under any desired set of test circumstances. With thedistributed processing system of the present invention, site performancetesting may be conducted using any number of real client systems 108,110 and 112, rather than simulated activity that is currently available.Several tests that are commonly desired are site load tests and qualityof service (QoS) tests. Quality of service (QoS) testing refers totesting a user's experience accessing a network site under normalusability situations. Load testing refers to testing what a particularnetwork site's infrastructure can handle in user interactions. Anextreme version of load testing is a denial-of-service attack, where asystem or group of systems intentionally attempt to overload andshut-down a network site. Advantageously, the current invention willhave actual systems testing network web sites, as opposed to simulatedtests for which others in the industry are capable.

Network site 106B and the multiple interactions represented bycommunication lines 116A, 116B and 116C are intended to represent a loadtesting environment. Network site 106A and the single interaction 116Ais indicative of a user interaction or QoS testing environment. It isnoted that load testing, QoS testing and any other site testing may beconducted with any number of interactions from client systems desired,and the timing of those interactions may be manipulated and controlledto achieve any desired testing parameters. It is further noted thatperiodically new load and breakdown statistics will be provided forcapacity planning.

FIG. 7B is a functional block diagram for a site-testing operation 700according to the present invention. Initially, client systems 108, 110and 112 receive workloads that identify testing procedures andparameters in the “clients receive testing workload” block 702.Following line 714, the client systems 108, 110 and 112 access the sitebeing tested and perform the testing in block “clients interact withother systems” block 704. Next, following lines 716 and 718, the clientsystems 108, 110 and 112 complete the site testing workload tasks, getthe results ready for transmission, and send those results back to thesystem server 104 in “clients complete testing workload” block 706 and“site testing results sent to server system” block 708. Control passesalong line 720 to “site testing results compiled for use” block 510where the server system formats and/or compiles the results for use bythe network site. For example, the site testing results may be utilizeddetermining modifications that need to be made to the network site tohandle peek volume activities.

FIG. 8 is a block diagram for a distributed processing system 800 for adata back-up system application, according to the present invention. Asstated above with respect to FIG. 1A, the network 102 may be a widevariety of networks, including an intranet network. Intranet networks,such as internal networks set up by corporations, are particularlysuited for this application because the systems holding the data beingbacked-up would be owned by the same entity owning other systems withexcess data storage capabilities. In this way, security would not be asgreat of an issue and the client system types could be bettercontrolled. It is noted, however, that this data back-up applicationwould be equally applicable to other networks, such as for computersystems connected through the Internet.

Referring back to FIG. 8, client systems 108, 110 . . . 112 are showneach having a back-up data blocks 804, 806 . . . 808. Customer systems152 is shown as having data 802, which is desired to be backed-up withthe distributed back-up system 800. The server systems 104 manage theflow of data from the data 802 and the client systems that have extrastorage space represented by back-up data blocks 804, 806 . . . 808. Inoperation, the server systems 104 identifies client system storagecapabilities. With this information, the server systems 104 can receivedata for back-up from any system on the network 102. It is noted, and asindicated with respect to FIG. 1A, the client systems 108, 110 . . . 112and the customer systems 152 may communicate directly with each other inpeer-to-peer type communications.

The servers systems 104 may also manage the storage and transfer of dataso that the data will be readily retrievable once backed-up and storedon the client systems 108, 110 . . . 112. If desired, an summary indexor directory of the backed-up data may be stored centrally on the serversystems 104, or may be stored remotely on the client systems 108, 110 .. . 112. It is also noted that the server systems 104 may alsodistribute data back-up workloads so that each portion of the data 802is stored redundantly on at least two of the client systems 108, 110 . .. 112. This redundancy provides added security should any one or moreclient systems suddenly cease to be operational.

Looking now to FIG. 9, a block diagram is depicted of an alternativerepresentation of an interconnection fabric for a distributed processingsystem environment 100, according to the present invention. In thisdiagram and as described above, the network environment may be theInternet, an internal company intranet, a local area network (LAN), awide area network (WAN), a wireless network, a home network, or anyother system that connects together multiple systems and devices. Inaddition, the server systems and clients systems may be interconnectedby a variety of possible connection interfaces, for example, Ethernetconnections, wireless connections, ISDN connections, DSL connections,modem dial-up connections, cable modem connections, direct T1 or T3connections, fiber optic connections, routers, portal computers, as wellas any other network or communication connection. It is noted,therefore, as discussed with respect to other embodiments such as theembodiment of FIG. 1A, that systems may be coupled into aninterconnected fabric in any of a variety of ways and communications canpotentially occur directly or indirectly between any of the systemscoupled into the fabric, as would be understood by those of skill in theart.

Within this environment, as depicted in FIG. 9, server systems 104 areinterconnected with any number of client systems, for example, clientsystems 108A, 108B, 108C, 108D, 108E, 108F, 108G, 108H, 108I, 108J, 108Kand 108L. In addition, these client systems may also include idle clientsystems 902A, 902B, and 902C, as discussed further below. Furthermore,these client systems may include client system 904A with a component A,client system 904B with a component B, and client system 904C with acomponent C. It is also noted that the interconnection fabric mayinclude any number of devices that are not client systems, in that theythemselves are not providing components or processing capabilities forthe distributed processing system of the present invention.Nevertheless, these devices may be considered part of the system becausethey may relay, interpret, process or otherwise transmit or receiveinformation from or to client systems that are part of the distributedprocessing system.

Aggregation of component level resources, according to the presentinvention, will now be discussed. As described above, the capabilitiesof client systems are determined for purposes of allocating, schedulingand managing distributed processing workloads. In other words, each ofthe client systems may be made up of many individual subsystems withvarious capabilities. In some cases, it may occur that particularcomponents on different machines may provide added value if combined oraggregated. Thus, utilizing subsystem or component level resources froma heterogeneous group of devices may be the most efficient or otherwiseadvantageous way of taking advantage of these resources to completevarious desired tasks.

Referring now more particularly to FIG. 9, the client systems 904A, 904Band 904C may have component A, component B and component C,respectively, that are better utilized in combination. For example,client system 904A may have a fast processor, a high-speed networkconnection, but little available storage space. Client system 904B mayhave large amounts of available free storage space but little processingpower. Client system 904C may also have a fast processor, but relativelylittle available storage space. In this example, a workload thatrequires both a large storage capacity and a fast processor may beefficiently completed by dedicating component level resources to variousparts of the workload from different machines. Thus, the workload may bemanaged by having client systems 904A and 904C processing data stored onand transmitted from client system 904B. Once clients systems 904A and904C process data, this resulting data may then be transmitted back toclient system 904B for aggregation and eventual transmission back to theserver systems 104. The client system 904B, therefore, essentially actsas a server for a workload subset, sending out portions of a subsetworkload, receiving back the processed data, and aggregating the data tobuild a completed workload subset.

It is noted that any number of different components from differentclient systems may be aggregated, as desired. For example, for wirelessdevices, DSP processing and storage components could be aggregated withcomponents from other client systems. For display devices, graphicsrendering power could be aggregated. For relatively dumb machines, suchas connected household appliances, vending machines, etc., slow-speedprocessing components could be aggregated. In short, an appropriateworkload may include instructions to numerous client systems that willenable collaboration and aggregation of component level resources. Suchinstructions may include things, such as, where to receive input, whereto send output, and ultimately which client systems return finalresults.

It is further noted that the control instructions may be de-centralizedas well. In other words, as indicated above, client systems maycommunicate directly with each other, for example, in a peer-to-peerfashion. In this way, workload communications may occur directly betweenclient systems, and workload control and management may occur throughthe client system agents located on client systems.

Still referring to FIG. 9, idle system determination will now bediscussed. As stated above, client system capabilities are determinedand utilized within the distributed processing system of the presentinvention. The more idle any particular client system, the moreprocessing it is arguably able to accomplish, and the more incentives itis likely to receive. In other words, the client system capabilities maybe utilized more often and more intensely if the client system is moreidle. As such, it is advantageous to identify idle client systems andallocate them to more processor and time sensitive tasks. By identifyingthese idle client systems, resources available on the network at anygiven time may be more fully utilized, and otherwise idle resources maybe utilized for highly intensive, real-time activities that wouldotherwise require dedicated devices. Examples of such real-timeactivities include data caching, indexing, etc. In FIG. 9, idle clientsystems are designated as 902A, 902B and 902C.

Identifying idle resources may be determined in any of a variety ofways. It is possible, for example, to simply look at whether a machineis not being used or has low processor utilization at any given time.This simple determination, however, may not yield an accurate picture ofhow idle a client system may or may not be over a given time period.More particularly, discovery methods may be implemented to identify theactivity of a variety of client system components and subsystems. Forexample, subsystems may be monitored, such as network activity, deviceoutput activity, user input, processing activity, executing taskmonitoring, or mode of operation parameters (e.g., mobile or powermanagement modes, stationary or powered mode). In addition, any numberof other device vectors may be monitored or analyzed to determine thetrue usage and idleness of a client system.

The following TABLE 2 provides a list of idleness vectors or factorsthat may be utilized in determining the level of device usage oridleness. In particular, TABLE 2 provides two primary categories ofactivities to monitor or analyze for determination of how idle a clientsystem may or may not be. These activities are user activity and deviceactivity. By monitoring, analyzing and tracking these client systemelements and activities over time, a better determination of deviceusage and idleness may be made. It is noted that the list provided inTABLE 2 is an example list, and any number of categories, vectors orfactors may be identified and utilized, as desired, according to thepresent invention.

TABLE 2 Example Client Idleness Vectors or Factors 1. User Activity(e.g., monitor input a. keyboard input activities, monitor outputactivities, monitor time elapsed since last input event and betweeninput events, etc.) b. mouse input c. microphone/voice input d. tabletinput e. pen input f. touch screen input g. joystick input h. gamepadinput i. video output j. printer output k. any other user activity thatcould be utilized to classify if a device is idle 2. Device Activity(e.g., monitor utilization a. power state (e.g., time since last powerlevels, monitor time elapsed since last state change event) deviceactivity, monitor time between changes in device utilization levels,etc.) b. mobility state (e.g., time since device c. screen saveractivity or trigger (e.g., last in mobile state) time elapsed sincescreensaver activity or trigger) d. screen output (e.g., time elapsedsince e. network or communication packets last screen output, paintevent or pixel sent or received (e.g., time elapsed change) since lastnetwork or communications activity) f. storage device activity (e.g.,time g. processor, DSP, microcontroller, elapsed since last storagedevice embedded device, or other processor activity, such as harddrives, flash activity (e.g., time elapsed since last memory cards,removable drives, CD processor activity) drives, DVD drives, etc.) h.processor, DSP, microcontroller, i. tasks or processes executing (e.g.,time embedded device, or other processing elapsed since change in numberof device utilization (e.g., change in tasks or processes executing)utilization levels) j. task or process device utilization (e.g., k. anyother device activity that could be time since change in task or processused to classify if a device is idle device utilization)

As a further example of the usefulness of this determination, referenceis made back to FIG. 9. Server systems 104 may have, for example, alarge, intensive task that it would like to place on these idle devices.After using a number of the vectors in TABLE 2 to determine theutilization level for client systems, the server systems 104 determinesthat client systems 902A, 902B and 902C are idle and capable of handlingsignificant time sensitive processing tasks. For example, idle clientsystems 902A, 902B and 902C may be personal computers that can act as alocal internet cache for other connected devices, such as some of theother client systems depicted in FIG. 9, that are interested in a datatype that benefits from a local network cache. Thus, data or content maybe transmitted from a remote network site to the idle machines 902A,902B and 902C. These idle devices 902A, 902B and 902C may thenre-transmit this same data or content to other connected devices alsointerested in the data or content.

One example for such network caching is Internet video or multimediabroadcast events that are desired to be viewed or received by a verylarge number of geographically close connected devices at about the sametime. In order to meet the demand of these connected devices, web sitesbroadcasting an event have to be able to handle a huge increase innetwork traffic over a short period of time. By locally caching thetransmission to idle client systems, a web site can reduce the directdemand on its own resources. This is so because other connected devicesmay receive a re-transmitted broadcast, although delayed, from the idleclient system. It is noted that according to the present invention idleclient systems 902A, 902B and 902C may work independently or incombination. Even though idle client systems are suited for providingthe caching function, it is also noted that that network caching may beaccomplished using one or more client systems regardless of theirrespective levels of idleness.

FIG. 10 is a more detailed block diagram for a client system agent 270installed on a client system, according to the present invention. Thisdiagram includes a security subsystem 1010, a capabilities subsystem1006, a workload processor 1004, a user interface 1002, and a projectmanagement and agent control subsystem 1008. The various components andsubsystems may communicate with each other, for example, through lines1012, 1014, 1016, 1018 and 1020. Externally, the client system agent 270may communicate through its security subsystem 1010 with the othercomponents within the client system and ultimately to other devicesconnected into the network fabric. It is noted that configuration of theclient system agent and its operation, both internal and external, maybe selected and designed, as desired.

As depicted, the capabilities subsystem 1006 includes an idle systemmonitor 1022, as described above, that monitors and analyzes user anddevice activities associated with the client system to determine thelevel of activity or idleness for the client system. The informationdetermined by this idle system monitor 1022 may then be communicatedexternally, for example, through the security subsystem 1010 to theserver systems 104. The server systems 104 may then store and analyzesystem idleness data from across the distributed processing system. Thisidleness data may become part of the capabilities database that isutilized to allocate and manage workloads and processing systemresources.

Still referring to FIG. 10, the workload processor 1004 includes amachine entry generation subsystem 1024. As described above, theworkload processor 1004 may send completed workloads back to serversystems 104 to generate sweepstakes entries for the host client system.In this way, when the incentive is a sweepstakes, the client system maygenerate entries by completing workloads. The machine entry generationsubsystem 1024 refers to this entry generation through workloadcompletion. As discussed above, the workload processed to generateentries may be a project workload, an entry workload, or any otherworkload, as desired.

FIGS. 11A and 11B provide more detailed flow diagrams of processembodiments for machine generated sweepstakes entries through processingof entry workloads, according to the present invention.

Looking first to FIG. 11A, an entry workload process flow 1100 isdepicted that provides machine generated sweepstakes entries. Processmoves from start block 1102 to block 1104 in which entry workloads areloaded on client systems. Next, process flows to block 1106 whichrepresents a periodic timer or other timing control for entry workloadprocessing. After this timing control, the client system executes orprocesses the entry workload in block 1108. In block 1110, a sweepstakesentry is thereby generated and returned to the server system 104 basedupon the completion of this entry workload. Process control then mayproceed back to the periodic timing block 1106, where timing controldetermines when the entry workload is next processed. The completedworkload represents the machine generated sweepstakes entry.

FIG. 11B is an alternative entry workload process flow 1150. The processflow 1150 is similar to the process flow 1100 except that the entryworkload is sent to the client system each time it is to be run. Processstarts in block 1102 and passes to the periodic timer block 1106, inwhich the process is controlled. For example, server systems 104 maydetermine when it is desirable for the client systems to receive andprocess an entry workload. In block 1104, the entry workload is sent tothe client systems. As with FIG. 11A, the client systems then executethe entry workload in block 1108, and an entry is generated and returnedto the remote server systems 104 in block 1110. The process thenproceeds back to the periodic timer 1106 until it is determined thatanother entry workload should be processed. The primary differencebetween process 1150 and process 1100 is that process 1150 is depictingan entry workload that is transmitted to the client system each time itis to be run.

One example utilizing the process 1150 or the process 1100 is forservers systems 104 to query the client systems for entry workloadprocessing at regular time intervals. If a distributed device returns acompleted entry workload back within a selected period of time from thedistribution of the entry workload, the server system may conclude thatthe distributed device should receive an entry because the distributeddevice is providing resources to the distributed processing system. Inthis way, the server systems 104 may determine at regular intervalswhether a given client system is working on project workloads for thedistributed processing system. Alternatively, the client system agentmay locally control the workload processing and may, for example, causethe client system to process and generate entries at regular timeintervals. It is noted that non-regular and varying time intervals mayalso be utilized and that combinations of remote and local control mayalso be utilized, as desired.

The timing of when a client system processes the entry workload,therefore, may be determined locally by the client system agent orremotely, for example, through commands sent by the server systems 104.In addition, periodic timing control may also be accomplished throughvarious combinations of control routines residing locally and remotely.It is further noted that any number of different variations may beutilized to provide machine generated entries to a sweepstakes,according to the present invention. Thus, a client system may generatesweepstakes entries in any of a variety of ways and still have machinegenerated sweepstakes entries, according to the present invention.

FIGS. 13A and 13B describe a data conversion application 1300 for amassively parallel distributed network according the present invention.In particular, FIG. 13A is a block diagram of a distributed processingsystem that provides data conversion services, according to the presentinvention. And FIG. 13B is a block flow diagram for data conversionservices within a distributed processing system, according to thepresent invention.

Converting file types, web pages, graphics images, etc., between devicetypes can be a highly intensive processing task. Example devices thatoften need converted data are wireless devices, such as pagers and cellphones, that request Internet web page information from their respectivedevice servers. The device server, instead of incurring the overhead ofreformatting the requested data for the wireless devices, may insteaddistribute the requested page or data address, the device typeinformation of the requesting device, and return address for thereformatted data. According to the present invention, the dataconversion, translation or processing may be performed by a clientsystem of the distributed processing system of the present invention.The resulting data may then be returned or provided to the originalrequesting device. In addition to data formatting for cell phones,language conversion, text translation and media translation services, orany other desired data conversion can also be hosted for a customerthrough the distributed processing system of the present invention.

It is noted that the data conversion operation contemplated by thepresent invention is not limited to any particular requesting device,any particular service provider, any particular type, of data to beprocessed, any particular type of resulting processed data, or anyparticular data source. Thus, the data processed may include voice,text, application, image, source code, or any other data type orcombination of data types, and the resulting processed data may alsoinclude voice, text, application, image, or any other data type orcombination of data types. According to the present invention, thedistributed processing system is utilized to process any data that isdesired by a requesting device and that must be converted or processedbefore being provided to the requesting device. For example, an end-userdevices connected to the Internet, such as personal computers, may signup for data conversion services through the server system so that theend-user device may request data conversion of any desired data, file,web site content, etc. Language translations and data formatting forconnected wireless are just two examples of such applications for thepresent invention.

Looking now to the embodiment of FIG. 13A, the network 102 is depictedas the Internet, and the requesting device is one or more wirelessdevices 1306 connected to the Internet 102 through communication links1308 and to the wireless device server systems 1304 throughcommunication link 1309. The data to be converted, translated orotherwise processed is represented by block 1302 and may be, forexample, content from an Internet web site that is connected to theInternet through communication link 1312. Also, as shown in FIG. 13A, amassively parallel distributed network (MPDN) server 104 is connected tothe Internet 102 through communication link 114. The wireless deviceserver systems 1304, or any other connected system that desires tooff-load data conversion processing requirements (e.g., web site contentservers), are connected to the Internet 102 through communication links1310 and to the MPDN server 104 through communication links 1311. Anynumber of client systems 108, 110 . . . 112 may also be connected to theInternet 102, through communications links 118, 120 . . . 122,respectively. As also stated above, any of the connected devices maycommunicate with each other in any of a wide variety of communicationtechniques (e.g., wireless, electrical, digital, analog, light-based,etc.) and protocols (e.g., static or dynamic IP addresses), and throughany number of other devices, as would be understood by one of skill inthe art.

In the application contemplated by FIG. 13A, the wireless devices 1306at times request data, for example, images or text from a web site, thatmust be converted, translated or otherwise processed by wireless deviceserver systems 1304 before it can be transmitted to, and displayed on, arequesting wireless device. Instead of converting the information, thewireless device servers systems 1304 may request that the MPDN server104 accomplish the data conversion or translation. The device serversystems 1304 may then provide to the MPDN server 104 any pertinentinformation, such as information concerning the requesting device, thenature of the data requested, and the processing needed for the data.The MPDN server 104 may then utilize one or more of the client systems108, 110 . . . 112 to process the data from block 1302 for transmissionto the requesting device. In this way, the wireless device serversystems 1304 may off-load burdensome and process-intensive conversiontasks to the distributed processing system of the present invention.

It is noted the transmission of processed data to the requestingwireless device 1306 may occur in a variety of ways. For example, theprocessed data may be transmitted from a client system 108 to the server104, then to the wireless device server 1304 and finally to the wirelessdevices 1306. Alternatively, the processed data may be transmitted froma client system to the wireless device server 1304, and then to thewireless devices 1306. Still further, the processed data may betransmitted directly from a client system to the wireless devices.

FIG. 13B provides a basic flow diagram for an embodiment of a dataconversion process 1350 according to the present invention. In block1352, a device, such as wireless devices 1306, requests unconverted,non-translated or non-processed data. In block 1354, a server for thedevice, such as wireless device server systems 1304, processes the datarequest and contacts the MPDN server 104. In addition, the contentprovider or server for the requested data, such as a web site contentserver, may contact the MPDN server 104. The wireless device serversystems 1304 provide all pertinent information to the MPDN server 104,such as the type of calling device, its identification, the relevantdata requested, and the conversion to take place. The MPDN server 104then distributes the data and information concerning the requestingdevice to one or more client systems, such as client systems 108, 110 .. . 112, in block 1356. The one or more client systems then convert,translate or otherwise process the data in block 1358. The converted,translated or processed data is then provided to the requesting devicein block 1360. Again, in this way, the device servers may provide a widerange of information without having to provide itself the processingpower to accomplish the conversion, translation or processing that isrequired to transmit or display the data on a requesting device.

As shown in FIG. 13B, the device server or the content server 1304 maycommunicate data and other pertinent information for a conversiondirectly to the client systems. For example, the MPDN server 104 mayprovide access to a group of client systems for data conversion purposesfor given periods time (e.g., monthly client group allocations), or mayprovide identities of groups of client systems that may be used at thetime a conversion is needed. Once the identity and allocation of clientsystems to a particular device server or content server is made, thedevice server or content server may communicate directly with the clientsystems. In addition, the device server or content server may providedirectly to a requesting device the identity of the one or more clientsystems accomplishing the data conversion. As shown in FIG. 13B, therequesting device, therefore, may communicate directly with the clientsystem or systems to provide pertinent information concerning the dataconversion requested. The client system may then, for example, directlydownload the desired content and perform the desired data conversion. Itis further noted that in addition to the embodiments described abovewith respect to FIGS. 13A and 13B, other methods for requesting,processing and providing data to and from the requesting device may beimplemented with distributed processing system of the present invention,such as caching processed data for later transmission.

FIGS. 14A and 14B depict example block diagrams of file distribution anddata sharing through the network fabric, according to the presentinvention. In particular, FIG. 14A depicts an Internet data filedistribution system 1400 that relies upon client systems to providelocal data distribution. FIG. 14B depicts a data file distributionsystem 1450 that allows for data sharing and rapid transmission of aproject or data files through the distributed processing system.

Looking now to FIG. 14A, a block diagram is depicted of a distributedprocessing system 1400 that provides data transmission caching or otherlocal distribution, according to the present invention. In theembodiment of FIG. 14A, server systems 104 are connected throughcommunication link 114 to the Internet back bone 1402. The Internet backbone 1402 represents the very high speed connections that carry datalong distances, for example, T3 or fiber optic lines that carry Internetdata across the United States. A web site 1404 is connected to theInternet back bone 1402 through communication link 1406, whichrepresents a geographically addition, the device server or contentserver may provide directly to a requesting device the identity of theone or more client systems accomplishing the data conversion. As shownin FIG. 13B, the requesting device, therefore, may communicate directlywith the client system or systems to provide pertinent informationconcerning the data conversion requested. The client system may then,for example, directly download the desired content and perform thedesired data conversion. It is further noted that in addition to theembodiments described above with respect to FIGS. 13A and 13B, othermethods for requesting, processing and providing data to and from therequesting device may be implemented with distributed processing systemof the present invention, such as caching processed data for latertransmission.

FIGS. 14A and 14B depict example block diagrams of file distribution anddata sharing through the network fabric, according to the presentinvention. In particular, FIG. 14A depicts an Internet data filedistribution system 1400 that relies upon client systems to providelocal data distribution. FIG. 14B depicts a data file distributionsystem 1450 that allows for data sharing and rapid transmission of aproject or data files through the distributed processing system.

Looking now to FIG. 14A, a block diagram is depicted of a distributedprocessing system 1400 that provides data transmission caching or otherlocal distribution, according to the present invention. In theembodiment of FIG. 14A, server systems 104 are connected throughcommunication link 114 to the Internet back bone 1402. The Internet backbone 1402 represents the very high speed connections that carry datalong distances, for example, T3 or fiber optic lines that carry Internetdata across the United States. A web site 1404 is connected to theInternet back bone 1402 through communication link 1406, whichrepresents a geographically communication links 1416A, 1416B and 1416C.It is noted that this caching will be aided if the client and non-clientdevices receiving the cached data are relatively short communicationhops from local distributor client device 1412E.

This data or network caching allows data to be streamed to an end userlevel device, which may then pass the data on to other end user devices.Thus, the downstream communications may be limited, thereby taking thedistribution burden off of the web site. For example, web site 1404 mayhave a large streaming video or multimedia file that is experiencing aheavy load from a given set of network devices. This data file may becached by a machine, such as client device 1412E, that is below from acommunication link 1410. Then, other devices that are also below thiscommunication link 1410 may download the streaming video data from theclient device 1412E. This caching eliminates the need to repeatedly sendthe same data through the same communication links to requesting devicesthat are located below common communication links. It is noted that thefile and data distribution possibilities for this peer file access,caching and data transmission, according to the present invention, arewide and varied and should not be seen as limited to the embodimentshown in FIG. 14A.

FIG. 14B is a block diagram of a distributed processing system 1450 thatprovides data distribution and data sharing, according to the presentinvention. As with FIG. 9, FIG. 14B depicts an alternative view of anetwork fabric that may interconnect any of a wide variety of devices.In the embodiment shown in FIG. 14B, server systems 104 areinterconnected with any number of client systems 108A, 108B, 108C, 108D,108E, 108F, 108G and 108H. Each of the connecting interconnectsrepresents any of a wide variety of communication links that may existbetween devices in the network fabric of the present invention. Each ofthe client systems 108A, 108B, 108C, 108D, 108E, 108F, 108G and 108Hinclude shared data (SD) according to the present invention. Within thisinterconnected fabric, block 1452 represents data or project informationthat is desired to be distributed. The SD blocks within each clientsystem facilitates the distribution of this data or project information.

A client agent, as discussed above, installed on the client systems108A, 108B, 108C, 108D, 108E, 108F, 108G and 108H includes functionalitythat facilitates a number of services with respect to data transmissionand sharing. First, the client agent provides a protected data storagearea accessible to outside devices, which is represented by the SD blockwithin each client system in FIG. 14B. This special storage spaceprotects the device from outside devices accessing other storage areason the device while allowing data to be shared and accessed by otherdevices and simultaneously used by the local client agent.

These shared data (SD) blocks provide mechanisms that enable a widevariety of possible interactions among the client systems 108A, 108B,108C, 108D, 108E, 108F, 108G and 108H. For example, the data sharingmechanism may provide a space for a cache of other device addressesattached to the network for both communication purposes as well assecurity purposes. The mechanism may also provide a simple indexingsystem that is automatically re-indexed when content is added or removedfrom the storage area. This indexing system may provide a mechanism forother client agents to perform discovery on the local client informationand visa versa. Through information stored within this shared data, thedistributed processing system of the present invention facilitates manydistributed file system applications such as distributed resume posting,distributed caching, distributed advertisement serving, etc. In additionto the above, the storage block (SD) within each client system mayinclude an interface for displaying or playing data types (such asimages, audio files, video files, etc.) stored both locally and/orremotely on other client devices. This would enable simple picturesharing, for example, between remote families connected via theinternet, as part of being a client system within the distributedprocessing system of the present invention.

In the embodiment shown in FIG. 14B, data or project 1452 is injectedinto the fabric through a connection to client system 108C and serversystems 104. These connections represent that the information may passfirst to servers systems 104, or may pass first to a client system, suchas client system 108C. It is noted that there are other ways that thedata may be injected into the fabric. Once injected, the data 1452 maybe transmitted throughout the fabric through any of a wide variety ofcommunications, including client-to-client, server-to-client,client-to-server, client-to-non-client, non-client-to-clientcommunications, and/or non-client-to-non-client communications. Thesecommunications may be based upon a variety of mechanisms, such aspolling mechanisms and pre-assigned firewall ports. This techniqueprovides a vehicle that facilitates the distribution of information to alarge number of devices in a short period of time.

Applications for this data distribution are wide a varied. For example,any important file that is time sensitive may be propagated to a largenumber of client devices, non-client devices, servers, or otherconnected devices, in a short amount of time. This transmission mayoccur quickly and efficiently once the information is injected into thedistributed processing system of the present invention. Example timesensitive data files are anti-virus signature files, which whendistributed through the distributed processing system of the presentinvention, may be transmitted through the network fabric faster than anew virus may normally proliferate.

Another application for rapid propagation of files is utilizing thistechnique for propagation of workloads. One example is distributedresume or job searching. In such a system, participating job seekers andparticipating employers may rapidly search for one another. A job seekermay inject a job request or search into the fabric that is then routedby each successive device to other devices without the need for controlfrom the server systems 104. Similarly, an employer may inject candidatecriteria into the fabric that is then routed to successive devices. Theresult is an extremely fast search and identification of employers andcandidates.

FIG. 15 is a block diagram of an alternative representation for adistributed processing system 100, according to the present invention.Server systems 104, database systems 1546 and web interface 1554 arecoupled together through communication links 1540, 1542 and 1544. Theweb interface 1554 includes clients subsystem 1548, task developersubsystem 1550, and advertisers subsystem 1552, and may include othersubsystems as desired. The database systems 1546 include workload (WL)information 308, client capability vector information 620, and any otherstored information as desired. Server systems include various modulesand subsystems, including database interface 1532, web server 1536, taskmodule and work unit manager 1530, client statistics module 1534,advertising manager 1538, task module version/phase control subsystem1528, sweepstakes engine 1524, server control subsystem 1526, andcommunication interface 1522. It is noted that in the embodiment of adistributed processing system 100 as depicted in of FIG. 15, the threeprimary operations for the server systems 104, database systems 1546 andweb interface 1554 are directed to managing, processing and providing aninterface for client systems, customer tasks, and customer advertising.

As discussed above, each client system includes a client agent thatoperates on the client system and manages the workloads and processes ofthe distributed processing system. As shown in FIG. 15, each of theclient agents 270A, 270B . . . 270C communicates with the server systems104 through communication links 1516, 1518 . . . 1520, respectively. Asdiscussed above, any number of different techniques and architecturesmay be utilized to provide these communication links. In the embodimentas shown in FIG. 15 with respect to client agent 270A, each client agentincludes a base distributed processing system component 1506 and aseparate project or workload component 1504. As depicted, acommunication interface 1508, a core agent module 1502, and a userinterface 1510 make up the base distributed processing system component1506. The task module 1512 and the work unit 1514 make up the separateproject or workload component 1504. The task module 1512 operates on topof the core agent module 1502 to provide processing of each project workunit 1514. It is noted that different or additional modules, subsystemsor components may be included within the client agent, as desired. Forexample, a personal computer screen saver component may be part of thebase distributed processing system component 1506 or the separateproject or workload component 1504.

Also as discussed above, security subsystems and interfaces may beincluded to provide for secure interactions between the various devicesand systems of the distributed processing system 100. As depicted inFIG. 15, a security subsystem and interface 1560 is interconnected withthe server systems 104, the database systems 1546, the web interface1554, and the client agents 270A, 270B . . . 270C. Theseinterconnections are represented by lines 1566, 1564, 1562, and 1568,respectively. The security subsystem and interface 1560 operates tosecure the communications and operations of the distributed processingsystem. This security subsystem and interface 1560 also represents avariety of potential security architectures, techniques and featuresthat may be utilized. This security may provide, for example,authentication of devices when they send and receive transmissions, sothat a sending device verifies the authenticity of the receiving deviceand/or the receiving device verifies the authenticity of the sendingdevice. In addition, this security may provide for encryption oftransmissions between the devices and systems of the distributedprocessing system. The security subsystem and interface 1560 may also beimplemented in a variety of ways, including utilizing securitysubsystems within each device or security measures shared among multipledevices, so that security is provided for all interactions of thedevices within the distributed processing system. In this way, forexample, security measures may be set in place to make sure that nounauthorized entry is made into the programming or operations of anyportion of the distributed processing system including the client agents270A, 270B . . . 270C.

In operation, client systems or end-users may utilize the clientssubsystem 1548 within the web interface 1554 to register, set userpreferences, check statistics, check sweepstakes entries, or accomplishany other user interface option made available, as desired. Advertisingcustomers may utilize the advertisers subsystem 1552 within the webinterface 1554 to register, add or modify banner or otheradvertisements, set up rules for serving advertisements, checkadvertising statistics (e.g., click statistics), or accomplish any otheradvertiser interface option made available, as desired. Customers andtheir respective task or project developers may utilize the taskdeveloper subsystem 1550 to access information within database systems1546 and modules within the server systems 104, such as theversion/phase control subsystem 1528, the task module and work unitmanager 1530, and the workload information 308. Customers may also checkproject results, add new work units, check defect reports, or accomplishany other customer or developer interface option made available, asdesired.

Advantageously, the customer or developer may provide the details of theproject to be processed, including specific program code and algorithmsthat will process the data, in addition to any data to be processed. Inthe embodiment shown in FIG. 15, this program code takes the form of atask module 1512 within the workload, while the data takes the form ofwork unit 1514. These two portions make up the project or workloadcomponent 1504 of each client agent 270. For a given project, the taskmodule 1512 will likely remain relatively constant, except for versionupdates, patches or phase modifications, while the work unit 1514 willlikely change each time processing of the data that it represents iscompleted. The project or workload component 1504 runs in conjunctionwith the base distributed processing system component 1506. When adifferent customer or project is started on a given client system, theproject or workload component 1504 will typically be replaced, while thebase distributed processing system component 1506 will likely remainrelatively constant, except for version updates, patches or othermodifications made for the distributed processing system.

Information sent from the servers systems 104 to the client agents 270A,270B . . . 270C may include task modules, data for work units, andadvertising information. Information sent from the client agents 270A,270B . . . 270C to the server systems 104 may include user information,system information and capabilities, current task module version andphase information, and results. The database systems 1546 may hold anyrelevant information desired, such as workload information (WL) 208 andclient capability vectors (CV) 620. Examples of information that may bestored include user information, client system information, clientplatform information, task modules, phase control information, versioninformation, work units, data, results, advertiser information,advertisement content, advertisement purchase information, advertisementrules, or any other pertinent information.

Further modifications and alternative embodiments of this invention willbe apparent to those skilled in the art in view of this description. Itwill be recognized, therefore, that the present invention is not limitedby these example arrangements. Accordingly, this description is to beconstrued as illustrative only and is for the purpose of teaching thoseskilled in the art the manner of carrying out the invention. It is to beunderstood that the forms of the invention herein shown and describedare to be taken as the presently preferred embodiments. Various changesmay be made in the shape, size and arrangement of parts. For example,equivalent elements may be substituted for those illustrated anddescribed herein, and certain features of the invention may be utilizedindependently of the use of other features, all as would be apparent toone skilled in the art after having the benefit of this description ofthe invention.

1. A method of operating a distributed processing system to provide dataconversion services, comprising: receiving a request from a requestingdevice for a data conversion of requested data; sending to a massivelyparallel distributed network (MPDN) server a type of the requestingdevice, an identity of the requesting device, the requested data, and atype of the data conversion, to enable the MPDN server to distribute thetype of the requesting device, the identity of the requesting device,the requested data, and the type of the data conversion to one or moreclient systems to complete the data conversion of the requested data;and enabling the one or more client systems to communicate a completeddata conversion result directly to the requesting device, wherein therequesting device is configured to receive the completed data conversionresult and at least one additional completed data conversion result, andwherein the requesting device is configured to assemble the completeddata conversion result and the at least one additional completed dataconversion result into a converted data set corresponding to therequested data.
 2. The method of claim 1 further comprising sending asoftware agent to the one or more client systems for completing the dataconversion of the requested data.
 3. The method of claim 1 furthercomprising: receiving one or more completed data conversion results fromthe one or more client systems; and assembling the one or more completeddata conversion results to generate the converted data set correspondingto the requested data.
 4. The method of claim 3 further comprisingsending the converted data set to the requesting device.
 5. The methodof claim 1, wherein the requesting device is a wireless device and thedata conversion of the requested data reformats a content of a networksite to generate a reformatted content that conforms to a protocol ofthe wireless device.
 6. The method of claim 1 further comprisingallocating the one or more client systems to perform the data conversionof the requested data for the requesting device with priority over otherprocessing the one or more client systems may perform.
 7. The method ofclaim 1, wherein enabling the MPDN server to distribute the type of therequesting device, the identity of the requesting device, the requesteddata, and the type of the data conversion depends upon capabilities ofthe one or more client systems.
 8. A massively parallel distributednetwork (MPDN) server configured to be coupled to distributed devices,wherein the distributed devices perform workloads for the distributedprocessing system, wherein the MPDN server is further configured to:receive a request generated by a requesting device for a data conversionof requested data, the request comprising a type of the requestingdevice, an identity of the requesting device, the requested data, and atype of the data conversion; partition the requested data intopartitioned data workloads; enable the distributed devices tocommunicate a completed data conversion result directly to therequesting device, wherein the requesting device is configured toreceive the completed data conversion result and at least one additionalcompleted data conversion result to assemble the completed dataconversion result and the at least one additional completed dataconversion result into a converted data set corresponding to therequested data; and distribute the partitioned data workloads, the typeof the requesting device, the identity of the requesting device, and thetype of the data conversion to the distributed devices to complete thedata conversion of the requested data.
 9. The MPDN server of claim 8,wherein the MPDN server is further configured to send a software agentto each of the distributed devices to perform the data conversion of oneof the partitioned data workloads.
 10. The MPDN server of claim 8,wherein the MPDN server is further configured to: receive completed dataconversion results from the distributed devices; and assemble thecompleted data conversion results to generate the converted data setcorresponding to the requested data.
 11. The MPDN server of claim 10,wherein the MPDN service is further configured to send the converteddata to the requesting device.
 12. The MPDN server of claim 8, whereinthe requesting device is a wireless device and the data conversion ofthe requested data reformats a content of a network site to generate areformatted content that conforms to a protocol of the wireless device.13. The MPDN server of claim 8, wherein the MPDN server is furtherconfigured to allocate at least one of the distributed devices toperform the data conversion of the requested data for the requestingdevice with priority over other processing the at least one of thedistributed devices may perform for the distributed processing system.14. The MPDN server of claim 8, wherein the MPDN server is furtherconfigured to determine sizes of the partitioned data workloads based onworkload capability factors of the distributed devices.
 15. The MPDNserver of claim 14, wherein the MPDN server is further configured todistribute the partitioned data workloads to the distributed devicesbased on the workload capability factors of the distributed devices,wherein the MPDN server distributes larger partitioned data workloads tocorresponding distributed devices with larger workload capabilityfactors.